Automated color control in film-to-digital transfer

ABSTRACT

A system and method for automatically adjusting color parameters during a film-to-digital transfer. An operator uses standard telecine equipment to preview scenes in order to determine a natural clustering of fields or scenes. Each cluster is processed separately. All the fields in a cluster are treated as one unit in the sense that color adjustments for the cluster are based on the cluster color histogram, which is computed by aggregating the colors from all pixels in the cluster. Constraints are specified for the cluster. Variables of a constraint may be automatically specified or determined by an operator based on observing sample frames from the cluster. In addition, the operator can nullify a constraint if desired. Within each cluster, the system adjusts red, green and blue intensities of the digitizing device, gains for each of these color channels, and other parameters. The system first determines which settings respect the constraints and then optimizes the solution. The solution is optimized such that the digital color distribution is as faithful as possible to the film color distribution subject to the constraints. This is achieved by adjusting the settings to maximize the entropy of the empirical, digital color histogram among all settings respecting the constraints.

PRIORITY

The present application claims priority from U.S. Provisional patentapplication No. 60/285,561 filed on Apr. 20, 2001, entitled “AutomatedColor Control in Film-to-Digital Transfer” which is incorporated byreference herein in its entirety.

BACKGROUND OF THE INVENTION

Film is commonly digitized and transferred either to digital tape or toa computer disk. Once the film is placed in digital form it may undergoadditional processing such as color correction, standards conversions,nonlinear editing, “panning and scanning,” compression, and/or variousforms of digital filtering.

In the process of correcting the color, the distribution of colors inthe film representation are balanced against the visual appearance thatthe colors have when displayed on a display device. Some of the desiredattributes take into account perceptual properties of the human visualsystem. Certain relationships among color components must be preservedso that, for example, “blacks appear black,” “whites appear white” andcolor tinted flesh tones appear natural. The corresponding relationshipsbetween color distributions and display devices are well-known toexperts. For example, it is known how red, green and blue should bemixed in order to look “black” on a given monitor, or to have theappearance of flesh.

The transfer from film to digital format is controllable through varioussettings on a digitization device which affect the intensities and otherproperties of the color components. The settings control for “lift”,“gamma,” “gain” and other standard parameters, are implemented digitallyfrom what is recorded to what is output. Some digitization devices allowfor the control of the exposure time of each color channel, therebyeffectively adjusting the three intensities. Although the details maydiffer from one device to another (corresponding to a different way ofimaging the film), the effects of adjusting the parameters can beobserved both mathematically by examining the color histogram andvisually by watching the video on standard monitors. In all currentsystems, an operator supervises the transfer, determines the propersettings for the variables, and is ready to make adjustments as may beneeded because of changing characteristics of the material. Inparticular, current systems are not automated.

SUMMARY OF THE INVENTION

A system for automatically adjusting intensity, gain and other colorparameters during a film-to-digital transfer is disclosed. The systemcan operate in a range of modes from fully automatic to fullyinteractive. The system collects statistics on the distribution of colorintensities in digitized film/video and automatically computesadjustments to the color intensity, gain and other settings in orderthat the visual appearance of the digital representation accommodatesstandard constraints on colors and color relationships. Theseconstraints may be determined automatically or in conjunction with anoperator. Among these constraints are that “blacks appear black” and“whites appear white,” that “clipping” and “banding” are limited, andthat there is proper “color balance.” It should be understood that manyother constraints may be defined for an image or a cluster (group ofimages) and that the constraints which are mentioned are only exemplary.A method for specifying and determining the optimal control settingsubject to the assembled constraints, namely the overall control settingwhich maximizes the information content of the observed colordistribution is also disclosed.

An operator uses standard telecine equipment to preview scenes in orderto determine a natural clustering of fields or scenes. Each cluster isprocessed separately. All the fields in a cluster are treated as oneunit in the sense that color adjustments for the cluster are based onthe cluster color histogram, which is computed by aggregating the colorsfrom all pixels in the cluster. Constraints are specified for thecluster variables of a constraint may be automatically specified ordetermined by an operator based on observing sample frames from thecluster. In addition, the operator can nullify a constraint if desired.Within each cluster, the system adjusts red, green and blue intensitiesof the digitizing device, gains for each of these color channels, andother parameters. The system first determines which settings respect theconstraints and then optimizes the solution. The solution is optimizedsuch that the digital color distribution is as faithful as possible tothe film color distribution subject to the constraints. This is achievedby adjusting the settings to maximize the entropy of the empirical,digital color histogram among all settings respecting the constraints.

Once the settings for a given cluster are determined, thefilm-to-digital transfer begins. The results of the ongoing transfer aretracked, checking that the current settings are adequate to continue toachieve good color balance, good contrast and good dynamic range.Settings are adjusted, scene by scene, as needed.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing features of the invention will be more readily understoodby reference to the following detailed description, taken with referenceto the accompanying drawings, in which:

FIG. 1 is a block diagram showing an exemplary system for automatingcolor correction functions;

FIG. 2A is a spatial representation showing all allowable controlsettings which is designated as the control space and a subset ofsettings labeled allowed settings which meet constraint criteria;

FIG. 3A shows a color histogram for film data which has been transferredto digital form but has not been color corrected;

FIG. 3B shows a color histogram for digital video which has been colorcorrected by a set of control settings which meets all constraints butis non optimal;

FIG. 3C shows a color histogram for digital video which has been colorcorrected by a set of control settings which meets all constraints andis an optimal solution exhibiting maximum entropy;

FIG. 4 is a flow chart of the steps for color control in film to digitalvideo transfers; and

FIG. 5 is a flow chart of the steps for color control in an alternativeembodiment.

DETAILED DESCRIPTION

It should be understood by one of ordinary skill in the art that film iscomposed of frames which are whole images while digital video isgenerally composed of fields which are one half of a whole film image.Video fields are either designated as odd or even corresponding to thelines of an image frame which are represented by the field. Digitalvideo may also be composed of frames representing a whole image from afilm frame. The term “frame” as used herein shall apply to both completeimages and also to interlaced image fields. The term “cluster” as usedherein refers to one or more frames (film/video). Generally a cluster isa group of frames which compose a scene or a group of scenes from afilm. Clusters can be designated by an operator or may be automaticallydetermined. The term “color information” shall refer to the digital datathat is associated with color. For example R,G,B values for a pixel,field, frame or cluster. The term “color parameter” includes but is notlimited to hue, saturation, and brightness. The term “control setting”as used herein refers to an arrangement of one or more color controlswherein each control sets a particular color parameter. A controlsetting causes color information from one or more film frames to bealtered. For example, a control setting may include a brightness level,a hue level, and a saturation level and will alter the R,G,B colorinformation.

It should be understood by one of ordinary skill in the art that colormay be represented in any of a number of color spaces such as Munsell,Ostwald, CIE, RGB, and YUV for example and the invention as disclosed isnot limited to any particular color space. Throughout this disclosure itis assumed that the intended display mechanism for the digital video isfixed such that any variations between displays is no longer a variable.

A system for color correction during a film-to-digital transfer is shownin FIG. 1. The system includes a digitization device 10 for receiving asinput film frames 12 and outputting a digital video sequence 14 composedof video fields or frames 13. The digitization device 10 samples thefilm and quantizes the color samples. In other embodiments, thedigitization device receives a digital sample of the film and provides amechanism for color correction. The digitization device is provided withadjustable controls 15 for changing color parameters 16 which adjuststhe color information 17 in the digital representation and as a resultthe visual appearance in any particular display mechanism. For example,each color may have an associated control 15 for independent adjustment,such that in an R,G,B color space all of the red values may be increasedor decreased. Similarly controls may alter groups of colors such thatthe hue, saturation or brightness may be changed. For example, thebrightness at high intensities can be adjusted to prevent “ballooning”and to get “soft clipping,” whereas brightness at low intensities can beadjusted to get sufficient detail in the dark areas of an image or acluster. Each possible control setting of these controls leads to adifferent color distribution of the color information for a cluster offrames.

A processor 20 executing software 25 interacts with the digitizationdevice for adjusting the color parameters 16 for a control setting 15 ofthe digitization device for the video transfer. Although the followingdescription shall refer to software, it should be understood by one ofordinary skill in the art that the software may be embodied on anintegrated circuit or may be a combination of computer code andhardware. The software can be set to adjust the colors of a cluster offilm frames either automatically or semi-automatically with input from ahuman operator. The software insures that conventional requirements onthe distribution of color information within each cluster of videoframes are satisfied while at the same time preserving information fromthe original distribution of colors.

The problem of color correction is formulated in the context ofconstrained optimization. The conventional requirements on thedistribution of colors will be referred to as “constraints”. Theconstraints are dependent on the display mechanism for the digital videorepresentation. Typical examples of constraints are “blacks should lookblack,” “whites should appear white,” and the overall average of thecolor channels should be “gray.” A further constraint is that human skinshould look like flesh. Other possible constraints are that there shouldbe limited “banding” and “clipping” in the dark and light areas of avideo image when it is displayed on a display device. Some constraintsare most naturally addressed in the RGB color space, whereas otherconstraints may be better addressed in other color spaces. The softwareis therefore provided with the ability to change between color spaces.For example, some of the color fidelity issues referred to below aregenerally address in “C_(b)/C_(r) color space”, referring to a colorcoordinate system based on a luminance or intensity variable Y=ρR+γG+βBwhere R, G, B stand for red, green and blue, and ρ, γ, β, are positiveparameters with ρ+γ+β=1. The other two components in this representationare C_(b)=Y−B and C_(y)=Y−R. Thus C_(b)/C_(r) space is simply a lineartransformation of R, G, B-space.

FIG. 2A shows a 2-D control space along with possible control settingswithin the control space wherein each control setting is indicated witha Θ. Each constraint may be represented as a property of an empiricalthree-dimensional histogram of colors related to the totality of pixelsin the corresponding sequence, which constitutes the cluster. Somecontrol settings yield a histogram which comply with the constraints,and some do not. The control settings which are within the space of allconstraints are represented with a Θ* while the optimum setting ismarked with a Θ**. The method for determining Θ** will be explainedbelow. FIG. 3A shows a representative 2-dimensional version of the 3-Dhistogram wherein only one color component is represented, which in thisexample is the color component red. This histogram represents thesampled color information from a cluster of frames prior to beingaltered by changes in the control settings of the digitization device.

FIGS. 3B–3C show altered 2-D color histograms of the histogram displayedin FIG. 3A. FIG. 3B shows a histogram wherein the control settings arechanged thereby altering the histogram. The settings used to produce thecolor information of FIG. 3B comply with all of the constraints andtherefore would reside within the shaded portion of the color spacerepresentation of FIG. 2A. FIG. 3C is also a histogram which containsaltered color information which complies with all of the constraints andrepresents the optimal solution Θ** from FIG. 2A.

Among the settings that respect the constraints, a method is defined forordering the solutions and therefore finding an optimal setting in thesense of sharing as much information as possible with the distributionof colors in the film representation. FIG. 4 is a flow chart showing thesteps used to determine such a control setting. First a set ofconstraints are determined (Step 401). Each constraint is a functionwhich depends upon the color information. The constraints are defined byone or more variables which may be either set by an operator orautomatically set within the constraint function. If the variables areautomatically set this step may be bypassed. The constraints as well asthe extent of automation of the constraints may be cluster-dependent.

A first constraint is color fidelity. Black regions in the original filmrepresentation should also look black (when the digital material isdisplayed), white regions should look white, flesh tones should appearnatural. All of these constraints are based upon human perception. Thecorresponding quantitative constraint on the color distribution can bedetermined either automatically, for instance by identifying peaks nearactual black (in a 3D color histogram of the color information) andrequiring that the colors of the corresponding pixels be black, or withthe assistance of an operator 5 manually specifying a spatial region inone or more frames in the cluster that needs to look black. In thepurely automated case, a constraint might be that a certain percentageof pixels for a cluster must be at full black (R,G,B,=0,0,0), forinstance 10% of all pixels.

In another variation which includes operator input, an operator couldadjust the percentage variable for the constraint.

The second constraint is balance, such that the overall mean of theempirical color distribution of the color information associated withthe cluster should be gray. This implies that the average color of allthe pixels in the cluster should lie on the diagonal (R=G=B) in thethree-dimensional color space. In an automated version the particularlevel of gray would be automatically chosen. In a semi-automatic mode ofoperation, the particular level of grey might be specified by theoperator.

Avoidance of clipping is another constraint. Clipping occurs when alarge number of pixels, usually very dark or very light, are assignedthe same quantization level in the color histogram. This results fromthe quantization problem wherein shades between two colors must beassociated with one of the two colors. Clipping is detected by searchingfor certain peaks in the histogram which are indicative of clipping.Such peaks normally occur at high or low light intensity levels andappear as a line on the histogram. Such lines in the histogram usuallyindicate that too much detail has been lost in the quantization processfrom the high resolution of film to the lower resolution of digitalvideo. The software can search for the slope of the line between pixelpoints having high or low light intensity levels to determine ifclipping is occurring. One method of implementing the constraint is toidentify a minimum slope in a set number of directions from a pixel forcompliance.

Another constraint is the noise level of the color information. Noiseoccurs when similar exposure values from the film get mapped to verydifferent color information values. Like the banding problem, noise isreflected in the shape of the color histogram, in this case, by gaps inthe dark areas which indicate that similar values on the film have beenmapped by the settings to very different values in the video realm. Thecorresponding constraint refers to the absence of such gaps. Theconstraint may be defined by a difference measurement in color betweenneighboring groups of pixels, such that if the difference measurementexceeds a threshold the constraint is complied with.

Clipping, banding and noise are relatively more objectionable in darkregions than in bright ones because the eye is more sensitive to detailin dark areas. Therefore, the constraints may be defined to be moresensitive for a certain black level. Taking into account one or more ofsuch phenomena leads finally to a series of constraints on the colorhistogram.

A digitized version of each film frame is either created through an A/Dconversion in a digitization device or a digitized version is importedwhich includes the color information (Step 402). The digital film isthen segmented into clusters which may contain one or more frames (Step403). The cluster may be manually selected by a human operator of thedigitization device or the cluster may be automatically created basedupon characteristics of the digital information as is known to one ofordinary skill in the art. In other embodiments, the film frames may bedivided into clusters prior to conversion to the digital domain.Further, it should be understood that the constraints may be definedafter the clusters are determined and in some embodiments in which theconstraints are cluster dependent this is the preferred sequence ofsteps.

A cluster is then selected for processing (Step 404). Controls of thedigitization device are then automatically set to a first setting of aplurality of possible settings which alters the color information forthe cluster (Step 405). It should be understood by one of ordinary skillin the art that the changes to the control settings may be done within aprocessor which is located within the digitization device. Further, itshould be understood that the number of control settings cannot be aninfinite number for a practical implementation. As a result, the controlspace having control settings must be limited to a finite number ofvalues. For instance, gain may have a scale from 0–1.0 which potentiallyhas an infinite number of levels however the parameter may be defined in0.001 increments such that there are 1000 finite levels. Similarly, thiswould hold true for all color parameters that make up a single controlsetting.

The adjusted color information is then analyzed to see if it complieswith all of the constraints (Step 406). If the color information of thecontrol setting does comply with all of the constraints then the controlsetting is saved (Step 407). If the color information does not complywith all of the constraints the control setting is discarded (Step 408)This process is continued iteratively until all of the possible settingswhich comply with the constraints are identified (Step 409).

More specifically, let F₁,F₂ . . . , F_(N) denote the video framescorresponding to a cluster, and consider a standard red, green, bluecolor representation so that F_(n)=(F_(n,r),F_(n,g),F_(n,b)), where inturn each of the three components is a mapping from a lattice of pixelsl to a range of intensity values, for example {0,1, . . . , 255} (“8 bitquantization”) or {0,1, . . . , 1023} (“10 bit quantization”). Supposethe lattice f is of dimension L×W. and let hist (r, g, b) represent thecolor histogram derived from the cluster. The histogram is based onN×L×W color samples and defined, for each color point (r, g, b) in {0,1. . . 2^(B)−1}³, where B is the number of bits in each color channel, asfollows:hist(r,g,b)=(NLW)⁻¹#{(n,x,y)∈{1,2, . . . ,N}×l: F _(n)(x,y)=(r,g,b)}wherein #{A} indicates the number of elements in the set A.

Let Θ represent the possible range of settings on the digitizationdevice. Thus each θ∈Θ corresponds to one control setting. Each suchsetting θ then determines a potentially different histogram. Thedependence on θ will be denoted by writing hist(r,g,b;θ). Theconstraints determine a subset of settings, namely those for whichhist(r,g,b;θ) displays the desired properties. Let Θ_(C)⊂Θ denote thecollection of control settings which comply with the constraints.

A score is then calculated for the control setting. (Step 410) The scoreis determined based upon the Shannon entropy of the color information.The entropy provides the mutual information between the distribution ofcolor in the and the digital representations subject to the constraints.This is true since each control setting may be regarded as aperturbation or quantization of the possible values of the film color,and hence as a function Y=g(X) where the random variable X representsthe original color information at a randomly chosen pixel. Thedistribution of X is dependent on the film content and afterquantization the number of possible values is reduced to a finitenumber. The maximization of the mutual information between X and Y is aquantization of original color values which produces a video colorhistogram sharing as much information as possible with the distributionof colors in the film representation. The optimal control setting isequivalent to the setting which maximizes the entropy of Y among allallowable control settings. This can be shown by:

I(X,Y)=H(Y)−H(Y|X) where H(Y|X) is the conditional entropy of Y given X.Since Y is a function of X, the conditional entropy of Y given X is zeroi.e. H(Y|X)=0. Consequently, maximizing the mutual information over allfunctions g is the same as maximizing the entropy H(g(X)) over all g.The entropy of g(X) depends only on the statistical distribution ofg(X), which in turn depends only on the particular function (controlsetting) g since the distribution of X is fixed and needn't beexplicitly considered.

For each θ∈Θ, the entropy of hist(r,g,b;θ) is

${H(\theta)} = {- {\sum\limits_{r,g,b}{{{hist}\left( {r,g,{b;\theta}} \right)}\log\mspace{11mu}{{hist}\left( {r,g,{b;\theta}} \right)}}}}$where the sum runs all 2^(3B) allowable (r,g,b) values and logrepresents log base 2.

The process repeats until all of the settings complying with theconstraints have assigned scores based upon the entropy of the colorinformation for the cluster. An optimal setting is then determined.Optimality is determined based upon the control setting with the highestscore. The optimal setting is defined to be the one setting whichsatisfies the constraints which maximizes the Shannon entropy. Theoptimal θ* is then defined by

$\theta^{\;*} = {\underset{\theta \in \Theta_{C}}{\arg\;\max}\;{{H(\theta)}.}}$

The corresponding histogram hist(r,g,b;θ*) then represents the digitalrepresentation which best matches the film representation subject to theconstraints.

The setting which provides the optimal score is preferably selected,although any setting, may be chosen which satisfies all of theconstraints (Step 411). This process continues until a control settingis chosen for all of the clusters (Step 412). Preferably the optimalcontrol setting is selected for all clusters, although control settingswhich comply with all of the constraints may also be selected. To findthe optimal control setting, optimization techniques which are known inthe art may be employed, such as global optimization. When certainconstraints do not provide a linear mapping, other optimizationtechniques, such as, gradient methods or sub-optimal solutions, such asmaximizing the score over a subset of control settings may be employed.It should be understood by one of ordinary skill in the art that widevariety of optimization techniques may be employed depending on theconstraint functions. The method thus adjusts the settings in order tomaximize the entropy of the color histogram, but confining the searchover settings to those which implement the constraints.

In another embodiment as shown in FIG. 5, the method for determining theoptimal control setting is determined by first iteratively processingcontrol settings until a control setting is found which meets all of theconstraints (Step 501). Next, the entropy of that control setting isdetermined as expressed above (Step 502). Another set of controlsettings, proximate to the original set of control settings in thecontrol space is then selected (Step 503). The entropy is calculated forthe proximate settings. (Step 504). The entropy values are thencompared. (Step 505). The control setting with the greater entropy isselected and saved. (Step 506). The process repeats to Step 503 whereinanother proximate control setting is selected from the control space.This process iteratively continues until the control setting in thecontrol space which exhibits the maximum entropy is found (Step 507).Computer code for searching for a maximum value is well known in the artand may be accomplished using many well known techniques.

In an alternative embodiment, the disclosed apparatus and method forautomated color control may be implemented as a computer program productfor use with a computer system including digitization devices. Suchimplementation may include a series of computer instructions fixedeither on a tangible medium, such as a computer readable medium (e.g., adiskette, CD-ROM, ROM, or fixed disk) or transmittable to a computersystem, via a modem or other interface device, such as a communicationsadapter connected to a network over a medium. The medium may be either atangible medium (e.g., optical or analog communications lines) or amedium implemented with wireless techniques (e.g., microwave, infraredor other transmission techniques). The series of computer instructionsembodies all or part of the functionality previously described hereinwith respect to the system. Those skilled in the art should appreciatethat such computer instructions can be written in a number ofprogramming languages for use with many computer architectures oroperating systems. Furthermore, such instructions may be stored in anymemory device, such as semiconductor, magnetic, optical or other memorydevices, and may be transmitted using any communications technology,such as optical, infrared, microwave, or other transmissiontechnologies. It is expected that such a computer program product may bedistributed as a removable medium with accompanying printed orelectronic documentation (e.g., shrink wrapped software), preloaded witha computer system (e.g., on system ROM or fixed disk), or distributedfrom a server or electronic bulletin board over the network (e.g., theInternet or World Wide Web). Of course, some embodiments of theinvention may be implemented as a combination of both software (e.g., acomputer program product) and hardware. Still other embodiments of theinvention are implemented as entirely hardware, or entirely software(e.g., a computer program product).

Although various exemplary embodiments of the invention have beendisclosed, it should be apparent to those skilled in the art thatvarious changes and modifications can be made which will achieve some ofthe advantages of the invention without departing from the true scope ofthe invention. These and other obvious modifications are intended to becovered by the appended claims.

1. A method for automated color control in converting film to digital video, the method comprising: receiving a digital video stream composed of a plurality of video frames, the plurality of video frames converted from film; partitioning the frames into a plurality of clusters, wherein at least one cluster contains a plurality of video frames and each cluster has an associated color distribution; automatically determining at least one modified color distribution for each cluster of digital video which complies with one or more color constraints for the cluster, the color constraints are evaluated on the color distribution of the cluster as a whole.
 2. The method according to claim 1 wherein there are a plurality of color constraints, the method further comprising: iteratively processing possible color distributions to identify any distributions which comply with all of the constraints.
 3. The method according to claim 2 further comprising: grading the color distributions according to entropy.
 4. The method according to claim 3 further comprising: selecting the color distribution which has the maximum entropy.
 5. A method for automated color control in converting film to digital video, the film being composed of frames containing color information defining one or more scenes the method comprising: converting the film frames into digital video frames; grouping the digital video frames into one or more clusters by scene; automatically determining altered color information for each cluster, wherein the altered color information complies with one or more color constraints, the color constraints are evaluated on the color information of the cluster as a whole and the altered color information for the cluster contains substantially the same color information as the film scene.
 6. The method according to claim 5 wherein the altered color information for each cluster is optimized such that the altered color information shares the maximum color information with the film scene subject to compliance with all color constraints.
 7. The method of claim 5 wherein the specified constraints include at least one of color fidelity, balance, absence of clipping, absence of banding and noise removal.
 8. The method of claim 5 wherein determining altered color information comprises adjusting color settings for a digitization device to maximize the entropy for the color setting.
 9. The method of claim 8 wherein adjusting the color settings comprises: calculating the entropy of the altered color information for each color setting; and selecting the color setting which satisfies the constraints and maximizes the entropy.
 10. The method of claim 9 wherein the color settings comprise at least one of lift, gamma and gain.
 11. The method of claim 8 further comprising: transferring the altered color information corresponding to the selected color setting to a digital medium.
 12. The method of claim 11 wherein the digital medium is digital tape.
 13. The method of claim 11 wherein the digital medium is a computer disk.
 14. A system for automated color control in converting film to digital video, the system comprising: a digitization device for converting frames of the film into digital video; means for partitioning the frames into a plurality of clusters, wherein at least one cluster includes a plurality of frames; means for specifying constraints for each cluster, the color constraints are evaluated on the color information of the cluster as a whole; and means for optimizing the color information in each cluster of digital video, wherein the optimized color information is as close as possible to the color information in the film subject to the constraints.
 15. The system of claim 14 wherein the constraints comprise at least one of color fidelity, balance, absence of clipping, absence of banding and noise removal.
 16. The system of claim 14 wherein the means for optimizing adjusts the color settings for each cluster to maximize the entropy among all possible color settings which respect the color constraints.
 17. The system of claim 14 wherein in adjusting the color settings the means for optimizing: calculates the entropy for each possible color setting complying with the color constraints; and selects the color setting which satisfies the constraints and maximizes the entropy.
 18. The system of claim 17 wherein the color settings comprise at least one of lift, gamma and gain.
 19. The system of claim 14 wherein the digitization device: transfers the color information to a digital medium.
 20. The method of claim 19 wherein the digital medium is digital tape.
 21. The method of claim 19 wherein the digital medium is a computer disk.
 22. A system for automated color control in converting film to digital video, the system comprising: a digitization device for converting frames of the film into a digital representation composed of color information; and an optimizer for optimizing the color information in each cluster of digital video, wherein the optimized color information is as close as possible to the color distribution in the film subject to specified constraints, the color constraints are evaluated on the color information of the cluster as a whole, wherein at least one cluster contains a plurality of digital video frames.
 23. The system of claim 22 wherein the constraints comprise at least one of color fidelity, balance, absence of clipping, absence of banding and noise removal.
 24. The system of claim 22 wherein the optimizer adjusts the digitization device according to a color setting for each cluster to maximize the entropy among all possible color settings which comply with the constraints.
 25. The system of claim 24 wherein in adjusting the optimizer: calculates the entropy for each color setting; and selects the color setting which satisfies the constraints and maximizes the entropy.
 26. The system of claim 25 wherein the color settings comprise at least one of lift, gamma and gain. 